Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "243"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 243 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 30 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 30 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 243, Node N19:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460013 RF_ok 100.00% 0.00% 0.00% 0.00% - - 21.066743 -1.036873 0.762213 -1.364736 1.876742 -0.417771 -1.336687 -0.070429 0.4314 0.5534 0.3574 nan nan
2460012 RF_ok 100.00% 0.00% 0.00% 0.00% - - 20.000055 -1.090988 0.589798 -1.505508 1.753706 -0.295663 -1.272303 -0.251606 0.4321 0.5562 0.3520 nan nan
2460011 RF_ok 100.00% 0.00% 0.00% 0.00% - - 15.577355 -1.109976 1.453064 -1.948931 7.994876 -0.600949 20.339347 -0.047541 0.4766 0.5559 0.3660 nan nan
2460010 RF_ok 100.00% 0.00% 0.00% 0.00% - - 20.387735 -0.794347 1.586901 -1.452470 5.864437 -1.188514 21.242586 -0.114385 0.4644 0.5698 0.3727 nan nan
2460009 RF_ok 100.00% 0.00% 0.00% 0.00% - - 20.630023 -1.461860 1.170478 -1.548941 3.079333 -0.487270 -0.299619 -0.139746 0.4533 0.5757 0.3776 nan nan
2460008 RF_ok 100.00% 0.00% 0.00% 0.00% - - 26.050259 -1.132771 1.230757 -1.716936 2.540372 -0.741322 0.567949 -1.358280 0.4905 0.6160 0.3386 nan nan
2460007 RF_ok 100.00% 0.00% 0.00% 0.00% - - 20.576456 -0.919178 0.752056 -1.168526 1.983611 -0.613492 -1.001724 0.117241 0.4506 0.5780 0.3609 nan nan
2459999 RF_ok 0.00% 0.00% 0.08% 0.00% - - nan nan nan nan nan nan nan nan 0.4802 0.6034 0.3291 nan nan
2459998 RF_ok 100.00% 0.00% 0.00% 0.00% - - 18.965366 -1.006053 0.851967 -1.180011 2.243730 -0.222856 -0.550485 0.341130 0.4556 0.5862 0.3793 nan nan
2459997 RF_ok 100.00% 0.00% 0.00% 0.00% - - 20.317753 -1.120882 1.108944 -1.180915 2.816525 -0.813413 -1.583066 -0.066349 0.4647 0.6004 0.3828 nan nan
2459996 RF_ok 100.00% 0.00% 0.00% 0.00% - - 20.821633 -1.374777 0.986236 -1.297616 2.739661 -1.044660 0.346544 -0.319375 0.4789 0.6093 0.3930 nan nan
2459995 RF_ok 100.00% 0.00% 0.00% 0.00% - - 21.580056 -1.166194 1.015272 -1.608310 2.471389 -0.094844 -0.924579 -0.364755 0.4661 0.6023 0.3819 nan nan
2459994 RF_ok 100.00% 0.00% 0.00% 0.00% - - 21.785811 -0.990931 1.042544 -1.237249 2.784365 -0.934426 -1.075764 -0.223917 0.4601 0.5941 0.3779 nan nan
2459993 RF_ok 100.00% 0.00% 0.00% 0.00% - - 25.702954 -1.059182 1.353535 -1.394347 3.706782 -0.335645 -0.392696 -0.049349 0.4404 0.5933 0.3894 nan nan
2459991 RF_ok 100.00% 99.89% 99.95% 0.00% - - nan nan inf inf nan nan nan nan 0.4806 0.2666 0.3979 nan nan
2459990 RF_ok 100.00% 0.00% 0.00% 0.00% - - 22.480895 -0.455912 1.242362 -1.368267 3.474895 -1.010285 -1.456681 -0.255564 0.4543 0.5858 0.3803 nan nan
2459989 RF_ok 100.00% 0.00% 0.00% 0.00% - - 22.410707 -0.501629 1.341922 -1.017412 2.897340 -0.804981 -0.975323 -0.166219 0.4553 0.5891 0.3820 nan nan
2459988 RF_ok 100.00% 0.00% 0.00% 0.00% - - 26.265284 -0.721889 1.250348 -1.484513 4.040368 -1.172142 -1.019285 -0.110985 0.4570 0.5923 0.3746 nan nan
2459987 RF_ok 100.00% 0.00% 0.00% 0.00% - - 21.045447 -0.973141 1.084995 -1.322734 2.197197 -0.563488 -1.045006 0.351328 0.4627 0.5955 0.3741 nan nan
2459986 RF_ok 100.00% 0.00% 0.00% 0.00% - - 25.629063 -0.955506 1.203189 -1.537571 3.656961 -1.334684 1.246472 -1.293508 0.4910 0.6261 0.3359 nan nan
2459985 RF_ok 100.00% 0.00% 0.00% 0.00% - - 23.719510 -1.001541 1.021288 -1.405942 2.406059 -1.174430 -0.486365 -0.025118 0.4677 0.5983 0.3797 nan nan
2459984 RF_ok 100.00% 0.00% 0.00% 0.00% - - 36.515554 -0.839168 0.640040 -1.432858 12.636936 -1.705085 5.398249 -0.768421 0.4148 0.6175 0.3793 nan nan
2459983 RF_ok 100.00% 6.59% 0.00% 0.00% - - 44.289744 -0.696904 0.374740 -1.428225 17.179438 -1.226231 23.155922 -0.934530 0.3720 0.6254 0.3864 nan nan
2459982 RF_ok 100.00% 0.11% 0.00% 0.00% - - 57.790797 -0.267569 0.288324 -0.936288 5.683998 -0.842556 4.822499 -0.831822 0.4250 0.6754 0.3996 nan nan
2459981 RF_ok 100.00% 0.00% 0.00% 0.00% - - 51.674956 -0.435476 0.994757 -1.494027 8.404720 -1.405663 39.218672 0.554868 0.3749 0.5953 0.4207 nan nan
2459980 RF_ok 100.00% 0.00% 0.00% 0.00% - - 50.476750 -0.777554 0.700655 -1.453843 5.387327 -1.426071 1.654094 -1.295189 0.4796 0.6446 0.3552 nan nan
2459979 RF_ok 100.00% 0.00% 0.00% 0.00% - - 52.370597 -0.507453 0.659828 -1.446666 6.989762 -1.133232 3.760459 0.088175 0.3990 0.5907 0.4128 nan nan
2459978 RF_ok 100.00% 0.00% 0.00% 0.00% - - 53.730029 -0.487011 0.824703 -1.573082 5.161532 -1.287010 4.751616 0.047776 0.3970 0.5902 0.4188 nan nan
2459977 RF_ok 100.00% 0.00% 0.00% 0.00% - - 52.296103 -0.627271 0.627492 -1.463131 8.819396 -1.557776 15.888445 -0.271163 0.3618 0.5518 0.3831 nan nan
2459976 RF_ok 100.00% 0.00% 0.00% 0.00% - - 54.348194 -0.570096 0.759778 -1.606147 4.705971 -0.809330 -0.778344 0.081211 0.4035 0.5986 0.4157 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 243: 2460013

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 21.066743 21.066743 -1.036873 0.762213 -1.364736 1.876742 -0.417771 -1.336687 -0.070429

Antenna 243: 2460012

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 20.000055 20.000055 -1.090988 0.589798 -1.505508 1.753706 -0.295663 -1.272303 -0.251606

Antenna 243: 2460011

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Temporal Discontinuties 20.339347 15.577355 -1.109976 1.453064 -1.948931 7.994876 -0.600949 20.339347 -0.047541

Antenna 243: 2460010

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Temporal Discontinuties 21.242586 20.387735 -0.794347 1.586901 -1.452470 5.864437 -1.188514 21.242586 -0.114385

Antenna 243: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 20.630023 20.630023 -1.461860 1.170478 -1.548941 3.079333 -0.487270 -0.299619 -0.139746

Antenna 243: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 26.050259 -1.132771 26.050259 -1.716936 1.230757 -0.741322 2.540372 -1.358280 0.567949

Antenna 243: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 20.576456 20.576456 -0.919178 0.752056 -1.168526 1.983611 -0.613492 -1.001724 0.117241

Antenna 243: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
243 N19 RF_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 243: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 18.965366 18.965366 -1.006053 0.851967 -1.180011 2.243730 -0.222856 -0.550485 0.341130

Antenna 243: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 20.317753 20.317753 -1.120882 1.108944 -1.180915 2.816525 -0.813413 -1.583066 -0.066349

Antenna 243: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 20.821633 20.821633 -1.374777 0.986236 -1.297616 2.739661 -1.044660 0.346544 -0.319375

Antenna 243: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 21.580056 21.580056 -1.166194 1.015272 -1.608310 2.471389 -0.094844 -0.924579 -0.364755

Antenna 243: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 21.785811 21.785811 -0.990931 1.042544 -1.237249 2.784365 -0.934426 -1.075764 -0.223917

Antenna 243: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 25.702954 25.702954 -1.059182 1.353535 -1.394347 3.706782 -0.335645 -0.392696 -0.049349

Antenna 243: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape nan nan nan inf inf nan nan nan nan

Antenna 243: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 22.480895 -0.455912 22.480895 -1.368267 1.242362 -1.010285 3.474895 -0.255564 -1.456681

Antenna 243: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 22.410707 -0.501629 22.410707 -1.017412 1.341922 -0.804981 2.897340 -0.166219 -0.975323

Antenna 243: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 26.265284 -0.721889 26.265284 -1.484513 1.250348 -1.172142 4.040368 -0.110985 -1.019285

Antenna 243: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 21.045447 21.045447 -0.973141 1.084995 -1.322734 2.197197 -0.563488 -1.045006 0.351328

Antenna 243: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 25.629063 -0.955506 25.629063 -1.537571 1.203189 -1.334684 3.656961 -1.293508 1.246472

Antenna 243: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 23.719510 -1.001541 23.719510 -1.405942 1.021288 -1.174430 2.406059 -0.025118 -0.486365

Antenna 243: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 36.515554 36.515554 -0.839168 0.640040 -1.432858 12.636936 -1.705085 5.398249 -0.768421

Antenna 243: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 44.289744 44.289744 -0.696904 0.374740 -1.428225 17.179438 -1.226231 23.155922 -0.934530

Antenna 243: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 57.790797 57.790797 -0.267569 0.288324 -0.936288 5.683998 -0.842556 4.822499 -0.831822

Antenna 243: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 51.674956 -0.435476 51.674956 -1.494027 0.994757 -1.405663 8.404720 0.554868 39.218672

Antenna 243: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 50.476750 -0.777554 50.476750 -1.453843 0.700655 -1.426071 5.387327 -1.295189 1.654094

Antenna 243: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 52.370597 52.370597 -0.507453 0.659828 -1.446666 6.989762 -1.133232 3.760459 0.088175

Antenna 243: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 53.730029 -0.487011 53.730029 -1.573082 0.824703 -1.287010 5.161532 0.047776 4.751616

Antenna 243: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 52.296103 52.296103 -0.627271 0.627492 -1.463131 8.819396 -1.557776 15.888445 -0.271163

Antenna 243: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
243 N19 RF_ok ee Shape 54.348194 -0.570096 54.348194 -1.606147 0.759778 -0.809330 4.705971 0.081211 -0.778344
In [ ]: